Effect of computerized cognitive training on mood, cognition, and serum brain-derived neurotrophic factor level in late-life depression — a pilot randomized controlled trial
Bibliographic record
Abstract
Background The aim of this pilot randomized controlled trial was to test the feasibility of a computerized cognitive training targeting executive dysfunction in late-life depression and to investigate its impact on mood, cognition, and brain-derived neurotrophic factor (BDNF) levels. Methods A total of 28 community-living Chinese individuals aged 55–75 with moderate-to-severe depression and cognitive symptoms (but without mild cognitive impairment or dementia) were recruited from a community centre in Hong Kong. Participants were randomly allocated to either the experimental (receiving computerized cognitive training) or the control group (receiving computer-based health education). Both programs lasted for one hour and were conducted twice a week for 6 weeks at the community centre. We assessed mood using the Hamilton Rating Scale for Depression (HAM-D) and Patient Health Questionaire-9 (PHQ-9), cognition using the Montreal Cognitive Assessment (MoCA), and serum BDNF levels at baseline and follow-up. We performed repeated measures analysis of variance to compare the differences in outcome changes between groups and correlation analysis to test if changes in mood and cognition correlated with changes in BDNF level. Results Our sample had a mean age of 66.8 (SD = 5.3) years, a mean HAM-D score of 19.4 (SD = 7.5), and a mean PHQ-9 score of 18.0 (SD = 6.3). No adverse effects were reported. Significant differences were observed between the experimental and control groups in changes in HAM-D (-8.4 vs. -2.9; group difference = -5.5; p = 0.01), PHQ-9 (-6.6 vs. -0.6; -6.0; p < 0.001), MoCA (1.4 vs. -1.3; 2.7; p = 0.001), and serum BDNF levels (in pg/ml; 2088.3 vs. -3277.4; 5365.6; p = 0.02). Additionally, changes in HAM-D, PHQ-9, and MoCA scores correlated significantly with changes in BDNF level. Conclusion With computerized cognitive training improving mood and cognition and increasing serum BDNF levels in 6 weeks, it may serve as a safe and effective evidence-based alternative or adjuvant treatment for late-life depression. Clinical trial registration https://www.chictr.org.cn/indexEN.html , identifier ChiCTR1900027029.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".